Validation of a genomic-clinical classifier for predicting clinical progression in high-risk prostate cancer.

2012 ◽  
Vol 30 (15_suppl) ◽  
pp. 4565-4565
Author(s):  
Christine Buerki ◽  
Anirban Pradip Mitra ◽  
Peter C. Black ◽  
Mercedeh Ghadessi ◽  
Eric J. Bergstralh ◽  
...  

4565 Background: The efficient delivery of adjuvant therapy after radical prostatectomy (RP) in patients with prostate cancer is limited by the lack of biomarkers, beyond clinicopathologic factors, that are able to assess the risk of clinically significant disease progression. Previously, routine FFPE patient specimens from the Mayo Clinic Radical Prostatectomy Registry with long term follow-up were selected to develop a genomic classifier (GC) to predict clinical progression. Here, we present the validation of a GC in a cohort of patients at high risk of disease progression. Methods: A case-cohort study of high-risk RP patients from the Mayo Clinic (N=219) was used to validate the genomic classifier (GC) for predicting clinical progression (defined by positive bone or CT scan post-RP). Its performance was compared to a multivariable clinical classifier (CC) and a genomic-clinical classifier (GCC) which combines GC with established clinicopathologic variables. Concordance index, Cox modeling and decision curve analysis were used to compare the different models. Results: GC and GCC were predictive of clinical progression in the high-risk cohort with c-indices of 0.79 and 0.82, respectively, compared to the clinical classifier (0.70). Multivariable survival analysis showed that the majority of prognostic information of GCC came from the GC with a minor contribution from Gleason score. Decision curve analysis showed that GCC had a higher overall net benefit compared to CC over a wide range of ‘decision-to-treat’ thresholds for the risk of progression. Conclusions: In this high-risk cohort, GC and GCC classifiers showed improved performance over CC in prediction of clinical progression. GC is an independent prognostic factor in this cohort and captures the majority of prognostic information. GC and GCC’s prognostic performance and their usefulness in guiding decision-making in the adjuvant setting after RP need further testing in studies of additional prostate cancer risk groups.

2021 ◽  
Author(s):  
Zhilei Zhang ◽  
Fei Qin ◽  
Guofeng Ma ◽  
Hang Yuan ◽  
Yongbo Yu ◽  
...  

Abstract Backgroud: This study was aimed to develop and internally validate a nomogram for risk of upgrade of ISUP (International Society of Urology Pathology) grade group from biopsy tissue to RP (radical prostatectomy) final histology.Methods: 166 patients with prostate cancer were retrospectively analyzed and divided into two groups based on ISUP upgrade status from needle biopsy to radical prostatectomy specimen, these being the 'ISUP upgrade' group and the 'no ISUP upgrade' group. Logistic regression analysis was used to predict the significant independent factors for ISUP upgrade. A nonogram was then developed based on these independent factors, which would predict risk of ISUP upgrade. The C-index, calibration plot, and decision curve analysis were used to assess the discrimination, calibration, and clinical usefulness of the predicting model. Internal validation was evaluated by using the bootstrapping validation. Results: There were 47 patients in the ISUP upgrade group and 119 patients in the no ISUP upgrade group respectively. Patients in the ISUP upgrade group tended to be of younger age, smaller PV (prostate volume), lower GS (Gleason score) of PB (prostate biopsy) tissue than the no ISUP upgrade group (p=0.043, p=0.041, p < 0.001, p =0.04, respectively). Multivariate logistic regression analysis showed that GS ≤6 (OR=14.236, P=0.001), prostate biopsy approach (TB-SB (transperineal prostate systematic biopsy) VS TR-SB (transrectal prostate systematic biopsy), OR=0.361, P=0.03) and number of positive cores < 10 (OR=0.396, P=0.04) were the independent risk factors for ISUP upgrade. A prediction nomogram model of ISUP upgrade was built based on these significant factors above, the area under the receiver operating characteristic (AUC) curve of which was 0.802. The C-index for the prediction nomogram was 0.798 (95%CI: 0.655–0.941) and the nomogram showed good calibration. High C-index value of 0.772 could still be reached in the interval validation. Decision curve analysis also demonstrated that the threshold value of RP-ISUP upgrade risk was 3% to 67%. Conclusion: A novel nomogram incorporating PSA, GS of PCa, ways of prostate biopsy and number of positive cores was built with a relatively good accuracy to assist clinicians to evaluate the risk of ISUP upgrade in the RP specimen, especially for the low-risk prostate cancer diagnosed by TR-SB.


2020 ◽  
Author(s):  
Zhilei Zhang ◽  
Fei Qin ◽  
Guofeng Ma ◽  
Hang Yuan ◽  
Yongbo Yu ◽  
...  

Abstract Backgroud: This study was aimed to develop and internally validate an ISUP (International Society of Urology Pathology) upgrade risk nomogram from the biopsy tissue to the specimen of radical prostatectomy. Methods: The clinical characteristics of 166 patients with prostate cancer were retrospectively analyzed, who were divided into two groups based on the upgrade of ISUP between the biopsy tissue and radical prostatectomy specimen. Logistic regression analysis was used to predict the significant independent factors of ISUP upgrade, a nomogram was established to predict ISUP upgrade of prostatectomy specimen based on the significant factors. The C-index, calibration plot, and decision curve analysis were used to assess the discrimination, calibration, and clinical usefulness of the predicting model. Internal validation was evaluated by using the bootstrapping validation. Results: There were 47 patients in the ISUP upgrade group and 119 patients in the no ISUP upgrade group respectively. Patients in the ISUP upgrade group inclined to be younger age, smaller PV, lower GS scores and PB-ISUP than the no ISUP upgrade group (p=0.043, p=0.041, p < 0.001, p =0.04, respectively), Multivariate logistic regression analysis showed that PSA≥20 ng/ml (OR=8.558, P=0.024), Gleason score of PCa≤6 (OR=9.026, P=0.004), PB-ISUP=3,4vs5 (OR=23.232, P=0.000417; OR=26.72, P=0.000241), ways of prostate biopsy (TP-SB+COG-TB (transperineal prostate biopsy + cognitive fusion targeted biopsy) VS TR-SB (transrectal prostate system biopsy), OR=033, P=0.036) and number of positive cores < 10 (OR=0.21, P=0.002) were the independent risk factors for ISUP upgrade. A prediction nomogram model of ISUP upgrade was built based on these significant factors above, the area under the receiver operating characteristic (AUC) curve of which was 0.843. The C-index for the prediction nomogram was 0.871 (95% CI: 0.817–0.925) and the nomogram showed good calibration. Decision curve analysis also demonstrated that the threshold value of RP-ISUP upgrade risk was 1% to 89%. Conclusion: A novel nomogram incorporating PSA, Gleason score of PCa, PB-ISUP, ways of prostate biopsy and number of positive cores was built with a relatively good accuracy to assist clinicians to evaluate the risk of ISUP upgrade in the radical prostatectomy specimen, especially for the low-risk prostate cancer diagnosed by TR-SB.


2007 ◽  
Vol 177 (4S) ◽  
pp. 130-130
Author(s):  
Markus Graefen ◽  
Jochen Walz ◽  
Andrea Gallina ◽  
Felix K.-H. Chun ◽  
Alwyn M. Reuther ◽  
...  

2005 ◽  
Vol 173 (4S) ◽  
pp. 222-222 ◽  
Author(s):  
Adam S. Kibel ◽  
Joel Picus ◽  
Michael S. Cookson ◽  
Bruce Roth ◽  
David F. Jarrard ◽  
...  

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